Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8844942 | Ecological Indicators | 2018 | 9 Pages |
Abstract
The vegetation status in China has undergone obvious changes since vegetation restoration projects were widely implemented in 1999. Based on a statistical analysis and the Hurst exponent index method, the spatial and temporal characteristics of vegetation change and its influence on runoff and sediment in China was analyzed using the Normalized Difference Vegetation Index (NDVI). The results showed that the change of vegetation coverage (E) in China from 2000 to 2015 was 5.64%. There was substantial variation in the spatial distribution of E values. There was a significant increase in the vegetation coverage in the areas covered by five vegetation restoration projects. It was found that 83.34% of the whole of China had experienced a continuous improvement in vegetation coverage. The largest increase in vegetation coverage occurred in the middle of the Loess Plateau and the middle of northeast China, while the largest decrease occurred in some areas of the Qinghai-Tibet Plateau and Xinjiang. Areas of vegetation degradation should be given special attention, with suitable control measures put in place. The slope angle with the largest increase in vegetation coverage was in the range of 15°-25°. Aspect had little effect on vegetation restoration. Vegetation restoration around the Hu Line, in which the precipitation was between 400 and 500â¯mm, was better and faster than in other regions. Vegetation coverage was linked to annual precipitation, and increased steadily with precipitation until a value of 500â¯mm was reached, after which it remained stable. Vegetation restoration did not reduce runoff, but it did reduce the sediment concentration. This study provided useful information for decision-makers involved in vegetation restoration projects and environmental management, especially in fragile ecological environments in arid and alpine areas.
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Authors
Guoce Xu, Jiaxin Zhang, Peng Li, Zhanbin Li, Kexin Lu, Xiukang Wang, Feichao Wang, Yuting Cheng, Bin Wang,